Texas Research Association (TRA) is a multidisciplinary research organization aimed on advancing the intersection of science and technology with the goal of publishing in national and international journals and conferences.
ScrollHere's exactly how this cycle works, from the first info session to onboarding. Attend one info session to be eligible to apply.
The research clubs are kind of siloed. You join one, you stick with one. TRA is not like that. We take people from CS, pre-med, physics, biology, and put them on the same team to work on the same problem. We started this because the most interesting work happens on the edge. The people who end up doing something new are the people who refused to specialize too early. You don't need to be a research person to be part of this. You just need to be curious, be willing to read things that are hard, and be willing to not know the answer.
We measure ourselves by work that leaves the building. One year in, here's where TRA research has landed.
A TRA year should feel like momentum, not a checklist. Scroll through the process the way it actually unfolds: one step pulls you into the next, and the end result is something public.
Studying whether models trained on overthinking-based rewards actually reason more efficiently, or simply learn to exploit the detector scoring them.
Comparing machine learning algorithms against CFD simulations to design drone propellers that maximize thrust while minimizing energy use.
Tracing how microplastics enter breastmilk, from ingestion mechanisms to detection methods, while exploring ways to reduce human exposure.
Investigating how combinations of post-translational modifications on intrinsically disordered proteins drive toxic aggregation in neurodegenerative disease.
Designing noise-resilient quantum circuits using multi-objective evolutionary architecture search for NISQ hardware.
Develops an AI model that predicts real-time organ viability during transport by identifying when an organ is at risk of decline enabling faster decision-making and optimized routing for transplant teams.
Investigating genetic mutations in ovarian cancer via data analysis and its correlation with PCOS.
Read and synthesize papers, design experiments, and understand what separates rigorous science from interesting speculation.
Write real code, build models, and ship things that actually run, not just slides.
Make sense of messy data and know when your results actually mean something.
Turn your work into papers, abstracts, and reports people can actually read.
Work across disciplines, lead a workstream, and figure out how to move a team forward when things are ambiguous, which they always are in research.
Info sessions, workshops, speaker events, and application deadlines, all in one place. Subscribe so you never miss one.
Open to any UT Austin undergrad. You don't need to have done research before, you just need to actually want to.
You must attend at least one info session before applying.